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Record W2734589110 · doi:10.7759/cureus.1462

Helical Tomotherapy for Postmastectomy Radiotherapy after Immediate Left Breast Reconstruction: A Case Study

2017· article· en· W2734589110 on OpenAlexaff
Dominique Mathieu, Nazanin Shahvary, Nicolas Côté, Kerianne Boulva, Léamarie Meloche‐Dumas, Toni Vu, Érica Patocskai, Christina Bernier, David Roberge, Israël Fortin

Bibliographic record

VenueCureus · 2017
Typearticle
Languageen
FieldBiochemistry, Genetics and Molecular Biology
TopicBreast Cancer Treatment Studies
Canadian institutionsCentre Hospitalier de l’Université de Montréal
FundersAmerican Association of Physicists in Medicine
KeywordsMedicineTomotherapyRadiation therapyAxillary lymph nodesMastectomyModified Radical MastectomySupraclavicular lymph nodesBreast cancerLymphRadiologySurgeryInternal medicineCancerPathology

Abstract

fetched live from OpenAlex

A 43-year-old premenopausal female presented with a multicentric infiltrating lobular carcinoma of the left breast with axillary nodes metastasis. She underwent modified radical mastectomy with axillary lymph node dissection (level I and II) followed by a mixed autologous latissimus dorsi flap reconstruction with the addition of prosthesis. The final pathological analysis revealed a 6 cm invasive lobular carcinoma pT3N2aM0, grade III/III, estrogen and progesterone positive, human epidermal growth factor receptor 2 (HER2) negative, with 5/16 positive lymph nodes. She received neoadjuvant chemotherapy with doxorubicin and cyclophosphamide followed by paclitaxel. Post-mastectomy radiotherapy with axillary, supraclavicular and internal mammary lymph nodes (IMLN) irradiation was delivered to a dose of 50 Gy/25 fx. In this case with multiple risk factors for radiation-induced cardiac toxicity (left-sided lesion, internal mammary lymph nodes (IMLN) irradiation), we discuss the role of helical tomotherapy as a treatment alternative to conventional tangential radiotherapy.

Fetched live from OpenAlex and de-inverted. Abstracts are not stored in this database: the inverted indexes are 8.6 GB of the frame’s 9.3 GB of text, and the host has 13 GB free.

How this classification was reachedexpand

Full frame machine prediction

Teacher imitation

Not calibrated prevalence, not ground truth. Human validation pending. The Gemma side is a direct model label for every work in the frame, read from the title-only record. The Codex side is a classifier learned from the 10,348 direct Codex labels and calibrated to design-weighted sample rates; fields without enough sample support carry no Codex call. Candidate is the union of the two sides; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels.

metaresearch head score (Codex)0.000
metaresearch head score (Gemma)0.001
Version: metacan-v3-hybrid-931329e0061cValidation status: machine_predicted_unvalidated
Candidate categoriesnone
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Case report · Consensus signal: Case report
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.003
Threshold uncertainty score0.011

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0000.001
Meta-epidemiology (narrow)0.0010.001
Meta-epidemiology (broad)0.0010.001
Bibliometrics0.0010.001
Science and technology studies0.0020.001
Scholarly communication0.0010.001
Open science0.0010.000
Research integrity0.0030.001
Insufficient payload (model declined to judge)0.0030.001

Machine scores (provisional)

The two teacher heads of the student model, read on this work. A score orders the frame for review; it never asserts a category, and the validation status ships verbatim with every row.

Baseline scores from an immature model (maturity gate not passed, 7 training rounds). Scores rank; they never assert a category.

Opus teacher head0.013
GPT teacher head0.300
Teacher spread0.287 · how far apart the two teachers sit on this one work
Validation statusscore_only:v0-immature-baseline · verbatim from the scoring run: score_only means the number may rank works, and no category label ships from it

Classification

machine, unvalidated

Machine predicted; a candidate call from one source (direct Gemma or distilled Codex), not a consensus.

The models applied no category: nothing in the taxonomy fit this work.
Study designCase report
Domainnot available
GenreEmpirical

How this classification was reached, model by model and score by score, is at the end of the page under "How this classification was reached".

Quick stats

Citations2
Published2017
Admission routes1
Has abstractyes

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